Chapter 9 True or False

On the basis of sample information, we either "accept the null hypothesis" or "reject the null hypothesis."

False

The alternative hypothesis typically agrees with the status quo.

False

The critical value approach specifies a range of values, also called the rejection region, such that if the value of the test statistic falls into this range, we do not reject the null hypothesis.

False

A hypothesis test regarding the population mean μ is based on the sampling distribution of the sample mean Xbar.

True

The null hypothesis typically corresponds to a presumed default state of nature.

True

Under the assumption that the null hypothesis is true as an equality, the p-value is the likelihood of observing a sample mean that is at least as extreme as the one derived from the given sample.

True

A Type II error is made when we reject the null hypothesis and the null hypothesis is actually false.

False

A Type I error is committed when we reject the null hypothesis which is actually true.

True

As a general guideline, we use the alternative hypothesis as a vehicle to establish something new, or contest the status quo, for which a corrective action may be required.

True

For a given sample size, any attempt to reduce the likelihood of making one type of error (Type I or Type II) will increase the likelihood of the other error.

True

In a one-tailed test, the rejection region is located under one tail (left or right) of the corresponding probability distribution, while in a two-tailed test this region is located under both tails.

True